Detection and monitoring of occupant seat belt

ABSTRACT

In one embodiment, a system of detecting seat belt operation in a vehicle includes at least one light source configured to emit a predetermined wavelength of light onto structures within the vehicle, wherein at least one of the structures is a passenger seat belt assembly having a pattern that reflects the predetermined wavelength at a preferred luminance. At least one 3-D time of flight camera is positioned in the vehicle to receive reflected light from the structures in the vehicle and provide images of the structures that distinguish the preferred luminance of the pattern from other structures in the vehicle. A computer processor connected to computer memory and the camera includes computer readable instructions causing the processor to reconstruct 3-D information in regard to respective images of the structures and calculate a depth measurement of the distance of the reflective pattern on the passenger seat belt assembly from the camera.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to and incorporates entirely byreference U.S. Patent Application Ser. No. 62/506,245 filed on May 15,2017, and entitled “Detection and Monitoring of Occupant Seat Belt.”

TECHNICAL FIELD

The disclosure presented herein relates to imaging systems within avehicle passenger cabin and is directed to locating, identifying, andhighlighting seat belt assemblies therein to confirm seat belt use andseat belt positions for respective vehicle occupants.

BACKGROUND

Seat belts are standard equipment for almost every kind of vehicle inwhich occupants are transported in today's transportation systems. Notonly are original equipment manufacturers (OEMs) required to meet strictstandards for seat belt engineering and installation, but in manyscenarios, vehicle occupants are required to wear seat belts as a matterof law. Even with manufacturing regulations and use laws in place,however, overall vehicle safety is entirely dependent upon vehicleoccupants using seat belts properly. Visual inspection by outsideauthorities is not completely reliable given that a vehicle interior isonly partially visible from outside of a vehicle. Individuals attemptingto circumvent seat belt use laws also position seat belts inside avehicle in a way that gives an appearance of seat belt use but allowsthe vehicle occupant more latitude in range of movement (i.e., fasteningthe seat belt behind the user's back or pulling the seat belt onlypartially across the user's body and manipulating the seat belt spool tomaintain the seat belt in an extended position without requiring a fixedlatching).

Seat belt misuse and/or unreliable seat belt monitoring may implicateissues other than simple bodily protection by restraining an occupantduring an accident. Detection and tracking of occupant seat belt use hasbeen primarily accomplished using on/off switches as sensors thattransmit corresponding buckled/unbuckled data signals to a centralprocessor as part of a vehicle control system data gathering operation.Sensor state from the seat belt switches can be used to determinerestraint settings and used, for example, to determine air bagsuppression or deployment decisions. Motorized seat belts may also usebelt payout sensors and/or belt tension sensors, where these sensors canbe used to detect and/or track proper belt placement as well as dynamicchanges in the seat belt payout when the occupant is moving. Suchsensors can be used to control restraint settings statically and/ordynamically.

Prior methods of seat belt monitoring can be effective but can also bespoofed. As noted above, individuals continue to engage in improper seatbelt buckling behind or under the occupant, attaching buckle surrogateswithout using the seat belt, and maneuvering themselves out of the seatbelt, particularly the shoulder strap, by hand. Furthermore, many rearseating locations do not currently use seatbelt switches, belt payoutsensors, or belt tension sensors. It may be difficult to install thenecessary electronics in adjustable and movable seating locations tosupport buckle switches, payout or tension sensors as aftermarketcontrol hardware.

A need continues to exist in the vehicle market for control systems thatmonitor vehicle occupants for proper seat belt use and provide seat beltuse and position data to the control system to enact additional safetyprecautions as discussed herein.

SUMMARY OF THE DISCLOSURE

In one embodiment, a system of detecting seat belt operation in avehicle includes at least one light source configured to emit apredetermined wavelength of light onto structures within the vehicle,wherein at least one of the structures is a passenger seat belt assemblyhaving a pattern that reflects the predetermined wavelength at apreferred luminance. At least one 3-D time of flight camera ispositioned in the vehicle to receive reflected light from the structuresin the vehicle and provide images of the structures that distinguish thepreferred luminance of the pattern from other structures in the vehicle.A computer processor connected to computer memory and the camera,includes computer readable instructions causing the processor toreconstruct 3-D information in regard to respective images of thestructures and calculate a depth measurement of the distance of thereflective pattern on the passenger seat belt assembly from the camera.

In another embodiment, the computer processor connected to computermemory and the camera has software enabling the processor to createrespective images of the structures and lot the images in a coordinatesystem, wherein the computer readable instructions are furtherconfigured to use the coordinate system to measure selected anglesbetween portions of the pattern on the passenger seat belt assembly andthe other structures in the vehicle.

In a third embodiment, a seat belt system includes an image detectorcomprising a sensor tuned to a selected wavelength for capturing animage on the sensor. A computer processor connected to computer memoryand the image detector is directed by computerized software instructionssuch that the processor receives the image and plots the image in a 3-Dcoordinate system. A seat belt assembly in the vehicle includes seatbelt components that incorporate reflective patterns thereon, whereinthe reflective patterns reflect light onto the sensor at the selectedwavelength and with a luminance that distinguishes the reflectivepatterns in the image. The image detector has a field of view sufficientto capture an image of at least one vehicle occupant operating the seatbelt assembly in the vehicle, and the computer readable instructionsaccessible by the processor adapt the 3-D information from the image foruse by an occupant classification system. The seat belt system providesverifying measurements computed from the 3-D coordinate system in regardto the position of the reflective patterns, the verifying measurementsbeing formatted for comparison with expected measurements according topreviously established standards presented by a classified occupantutilizing the seat belt assembly.

In yet another embodiment, a system of evaluating seat belt assembliesinstalled in a vehicle includes at least one camera connected to acomputer system and at least one light source that illuminates regionsof interest within a vehicle, wherein at least one region of interest iswithin the at least one camera's field of view. At least one seat beltassembly is installed in the vehicle and positioned within the at leastone camera field of view, and the seat belt assembly includes fixedcomponents that are stationary in the vehicle and dynamic componentsthat move within the vehicle, the fixed and dynamic components includingrespective patterns that each have a predetermined reflectivity. Thecomputer system includes at least one processor connected to memoryhaving computer implemented instructions thereon, and the computer isimplemented with instructions configured to use the camera to generateat least one image of the at least one region of interest in thevehicle; identify at least one fixed component of the at least one seatbelt assembly as a reference component within the image of the region ofinterest; calculate at least one reference measurement as the distancebetween the camera and an identified pattern in the image as reflectedfrom the reference component; calculate respective spatial measurementsof dynamic components of the seat belt assembly as captured in theimage, wherein the respective spatial measurements of the dynamiccomponents comprise distances between selected patterns reflected fromthe dynamic components as shown in the image and other structures withinthe vehicle also shown in the image; and compare the spatialmeasurements of the dynamic components of the seat belt assemblyrelative to the reference measurement to evaluate the seat belt assemblyin the vehicle.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a plan view of a vehicle interior having seats installedwithin respective fields of view of cameras in the vehicle.

FIG. 2 is a perspective view of a seat belt assembly having reflectivepatterns thereon as described herein.

FIG. 3 is a perspective view of a seat belt buckle component in abuckled position with a seat belt tongue affixed thereto.

FIG. 4 is a representative 3-D image captured by the cameras of FIG. 1.

FIG. 5 is a portion of the image of FIG. 4 cropped for a particularregion of interest.

FIG. 6 is a portion of the image of FIG. 4 showing a visuallyobstructing item within the particular region of interest.

FIG. 7A is a perspective view of a vehicle interior captured as one of aseries of 3-D image analysis screens provided by a computer associatedwith the system described herein.

FIG. 7B is a schematic view of a selected seat belt pattern captured inthe series of 3-D analysis screens of FIG. 7A.

FIG. 7C is a schematic view of a two-dimensional cross-correlation imageof a vehicle interior captured in the series of 3-D analysis screens ofFIG. 7A.

FIG. 7D is a schematic plot of a one-dimensional version of a crosscorrelation signal plotted from the two-dimensional image of FIG. 7C.

FIG. 8A is a perspective view of a camera used for capturing a series ofimages illustrating an establishment of fixed reference points within avehicle.

FIG. 8B is a schematic representation of a first captured view of areference target within a vehicle interior as disclosed herein.

FIG. 8C is a 3-D image of a vehicle occupant and reference target shownschematically in FIG. 8B.

FIG. 8D is a reduced resolution 3-D image of a vehicle occupant and aseries of reference targets positioned within a vehicle interior.

FIG. 8E is a schematic representation of a measuring and positioningfunction enabled by a vehicle camera as disclosed herein.

FIG. 9 is a schematic drawing showing an establishment of fixedreference points from otherwise dynamic structures in a vehicle.

FIG. 10 is an intensity image captured with a vehicle interior camera asdisclosed herein.

FIG. 11 is a schematic representation of a camera field of view that isadjustable within a vehicle interior as disclosed herein.

FIG. 12 is a schematic representation of an intensity image for a seriesof fixed reference points in a vehicle interior as disclosed herein.

FIG. 13 is schematic representation of a depth image for a series offixed references points in vehicle interior as disclosed herein.

FIG. 14 is a schematic representation of a plot of image frames showingreference target distances in centimeters as captured by a cameraaccording to the disclosure herein.

FIG. 15 is a two-dimensional reflected intensity and distance imageillustrating an establishment of fixed reference points within a vehicleas shown in FIG. 9.

FIG. 16 shows a series of 3-D analyses for range accuracy of imagesacquired according to the disclosure herein.

FIG. 17 shows a series of 3-D analyses of RMS error values associatedwith images acquired according to the disclosure herein.

FIG. 18 shows a series of 3-D analyses of residual data for imagesacquired according to the disclosure herein.

FIG. 19A is a first perspective view of a timed series of five images(A-E) illustrating tracked motion of a seat belt component utilizingfixed references as disclosed herein.

FIG. 19B is a second perspective view of a timed series of five images(A-E) illustrating tracked motion of a seat belt component utilizingfixed references as disclosed herein.

FIG. 19C is a third perspective view of a timed series time series offive images (A-E) illustrating tracked motion of a seat belt componentutilizing fixed references as disclosed herein.

FIG. 19D is a fourth perspective view of a timed series of five images(A-E) illustrating tracked motion of a seat belt component utilizingfixed references as disclosed herein.

FIG. 19E is a fifth perspective view of a timed series of five images(A-E) illustrating tracked motion of a seat belt component utilizingfixed references as disclosed herein.

FIG. 19F is a sixth perspective view of a timed series of five images(A-E) illustrating tracked motion of a seat belt component utilizingfixed references as disclosed herein.

FIG. 20 is a plot of reference distance versus time for images acquiredaccording to the disclosure of FIG. 19.

FIG. 21 is a plot of reference corrected and averaged signals for imagesacquired according to the disclosure of FIG. 19.

FIG. 22 is a plot of averaged signal and low pass filtered signalsimages acquired according to the disclosure of FIG. 19.

FIG. 23 show a series of 3-D analyses of images acquired according tothe disclosure of FIG. 19.

DETAILED WRITTEN DESCRIPTION Overview

This disclosure uses electromagnetic sensor(s) to detect positions ofnumerous components of a seat belt assembly and track seat belt usewithin a vehicle. In one embodiment, the sensor is an active optical 3-Dtime of flight imaging system which emits a known waveform (e.g.sinusoidal, pseudo-random, and the like) of electromagneticwavelength(s) of light which are collocated and/or synchronized with a2-D imager detector array where the amplitude of the detected signal isproportional to the reflected light at the light wavelength(s). Usingwell known techniques, such a sensor can collect both the reflectedlight intensity of surfaces in the field of view of the imager and thedistance of the surface from the imager detector.

The light is emitted and hits the surface of all objects within a lineof site. As a function of the geometric arrangement and compositionalmaterials of the object, a portion of the light is reflected backtowards an imager detector array. Signal processing of the detectedsignals can be used to reconstruct 3-D information (intensity image anddepth image) which can be used in machine vision algorithms to detect,and/or classify, and/or track information about the objects within thescene. In one non-limiting example embodiment, the light sourcewavelength may be selected as 950 nm, and the source of the selectedlight could be an LED array or VCSEL laser(s) with dispersion/filteringoptics to disperse light within a known spatial area. Without limitingthis disclosure to one kind of equipment set-up, the imager array maybe, for example, a silicon multi-pixel array synchronized and sensitiveto the above described 950 nm light emitted from a corresponding lightsource. However, the sensor and associated sources and detectors couldalso be based on other electromagnetic methods such as passive opticalimagers (2-D, using ambient lighting) radar, ultrasonic, microwave, andnumerous detection technologies.

In example embodiments, the seat belt material and/or the mechanicalmounting of the seat belts (e.g. seat belt payout aperture) and/ormechanical features on the seat belt (e.g. d-rings, retention buttons,etc.) are composed of materials and/or augmented with an appropriatepattern such that features within the pattern have a controlled,deterministic reflectivity in the sensor wavelength region(s). Forexample, the seatbelt material can be coated (or sewn) with aninterchanging pattern of high and low reflectivity materials (712) atthe selected sensor wavelength(s). The pattern can be selected toprovide improved ability to detect and track information about the seatbelt by either visual inspection or by image detection in an automatedcomputer vision system. Machine vision methods can be optimized todetect, classify and track these patterns. Pattern features may beselected for optimal contrast to detect/track extent of seat beltpayout, depth of seat belt, and other comparative data sets, such aswhich belt position is in a closest position to camera (e.g., toidentify the occupant's chest). Embodiments described herein detect,monitor, and/or track seat belt payout apertures and seat belt patterns,wherever located in an image created from a camera field of view. Forexample, these patterns can be located in seats, on roofs or in vehicleside structures to detect positions of seat belts or portions thereofrelative to occupant body anatomy (e.g., shoulder/head).

In cases where the belt may be obscured by occupant appendages, objectsbrought into a vehicle by the occupant, such as clothing, blankets,luggage, cargo, or anything that the occupant places over an expectedarea for a seat belt can be accounted for in this system. The system andmethods described herein identify reference points within a space thatare significantly less likely to be obscured in a vehicle, providingknown structures from which to evaluate seat belt use and operation. Byidentifying reference structures that are always visible within avehicle, the system and methods disclosed herein take advantage ofpartially visible portions of a seat belt assembly, along with occupantclassification methods, to predict proper or improper seat belt use. Thedetailed description below explains more embodiments of the methods andsystems for seat belt monitoring in accordance with the figuresreferenced therein.

FIG. 1 is an overview schematic of a vehicle according to thisdisclosure including rows of seats (13A, 13B, 13C) within the interior(10), or cabin, of a vehicle. The term “vehicle” as used herein includesall of the broadest plain meanings for the term within the context oftransportation (i.e., any references to an automobile are for examplepurposes only and do not limit this disclosure to any one embodiment).The vehicle of FIG. 1 incorporates a driver' seat (13A) adjacent asteering wheel (19) and a common driver's control panel (17) (possiblyincluding a viewing screen). The vehicle control system is not shownseparately but would include processors, memory, electronic circuits,and sensor necessary to establish a safe driving environment in thevehicle interior (10). The computers (27) in the vehicle may communicatewith occupant classification systems (21) used to determine theentry/exit location anatomy, age, adult/child/infant status, and otherquantitative characteristics of each occupant in the vehicle. Thevehicle of FIG. 1 would typically include standard OEM equipment such asseat belt assemblies shown in more detail in other figures. The vehicleof FIG. 1, however, illustrates installation of cameras (12A, 12B, 12C)having respective light sources and positioned in the vehicle interior(10) to establish respective fields of view of occupants, seats (13),seat belt assemblies (20A, 20B), and other structures in the vehicle. Inthis non-limiting example, the cameras/image sensors (12) have beeninstalled on the ceiling (15) of the vehicle and atop the driver'scontrol panel (17). The vehicle includes the associated circuitry toconnect the cameras (12), light sources (16), and associatedarrays/sensors (hereinafter “image sensors” (14)) to a vehicle controlsystem operating via a computer bank (11).

FIG. 2 illustrates more details about the vehicle interior (10) and theseats (13) with seat belt assemblies (20A, 20B) operating therein. Onenon-limiting aspect of this disclosure includes utilizing components ofthe seat belt assembly (20A, 20B) in a way that maximizes seat beltmonitoring capabilities. The components may include, but are not limitedto, a seat belt retractor assembly (i.e., a spool that unwinds andre-winds the seat belt into a webbing payout section (44)), a payoutaperture (30) through which a seat belt extends, a portion of a seatbelt assembly configured as a shoulder strap (48), a lap strap (36), alap belt anchor (32), web length adjustment hardware (34), a buckle(40), buckle hardware (35), a seat belt tongue (42), at least one face(46) of the seat belt buckle (40), and peripheral hardware used toinstall or enable the seat belt assembly functions (e.g. d-rings,retention buttons). The term “seat belt hardware” is not intended to belimiting of this disclosure and includes any structure of the seat beltassembly that provides any kind of connection, installation, oroperation function relative to the lap strap and shoulder strap shown inFIG. 2. At least these components may include patterns that are integralwith, applied to, or manufactured with a respective component. Thepatterns are designed of materials having a known reflectivity such thatthe pattern is distinguishable in an intensity and/or distance imagetaken of the vehicle interior (10). A pattern having a pre-determinedreflectivity due to its material composition shows up with adistinguishable luminance (or visible intensity) sufficient todistinguish the pattern from other structures in an image. The patternmay show up in an image as either a lower luminance region or a higherluminance region at the preference of the designer and continue to beuseful for distinguishing components of the seat belt assembly. In FIG.2, components of the seat belt assembly (20) show respective shoulderstrap patterns (38), belt patterns (50), webbing payout section patterns(52), buckle aperture patterns (53), buckle pattern (56), and differentpatterns on opposite sides of components (i.e., opposite sides of thelap strap and shoulder strap having different patterns can identify atwisted position for a seat belt in an associated image.

FIG. 2 illustrates certain components that may be significantly visibleat all times in the vehicle interior (10) even when an occupant or anoccupant's belongings obscure other portions of the seat belt assemblyfrom the camera field of view. For example, a webbing payout section(44) such as an area defined within a b pillar in a vehicle may beinstalled at multiple sites within the vehicle interior to provide apay-out of an associated seat belt across an occupant. The retractorcase and an associated payout aperture (30) would typically be visibleto a properly positioned camera, even if the occupant holds an obscuringobject (33) in the occupant's lap as illustrated in FIG. 6. Other kindsof components that are less likely to be hidden by cargo and usuallyvisible within a camera's field of view include the seat belt buckle(40), which has a known range of motion.

FIG. 3 illustrates a blown up view of a seat belt buckle havingrespective patterns on certain sub-components of the buckle component.For example, a shoulder strap (48) has a first shoulder strap pattern(38) on one side that can be identified as stripes and a second shoulderstrap pattern (50) on an opposite side. In the example of FIG. 3, theopposite side of the shoulder strap is also visible as a lap beltpattern (50) for an associated lap strap (36). The buckle (40), thetongue (42), buckle faces (46), and web length adjustment hardware (34)are all viable candidates for having an identifiable pattern thereon.

FIG. 4 shows one example embodiment of at least three seat beltassemblies (20) in use within a vehicle interior (10), and each seatbelt assembly is operable with a respective seat (13A, 13B, 13C) havinga different occupant therein. As would be true in most scenarios, theoccupants are distinctive in both size, shape, and dimensions that canaffect proper seat belt position for each occupant. The image of FIG. 4illustrates an example of one kind of image (80) that a vehicle camera(12) (or an appropriate system of multiple cameras) can produce from aproperly tuned light source (16) illuminating the vehicle interior (10)at a wavelength of electromagnetic radiation/light waves that has beenselected to correspond to the capturing sensitivities and resolution ofan image sensor (14) receiving reflected light back from materials andobjects within the camera field of view. The image (80) may be either atwo dimensional or three dimensional image, depending on the camera, thearray, and the associated computer processors, but the patterns on theseat belts, anchor points, and retractors are visible therein. Thepayout aperture (30) within each webbing payout section (44) isillustrated with a significantly prominent pattern (52) outlining theaperture so that an origin of seat belt payout may be distinguishable inthe image. The case (44) may have a different pattern (45) to furtherilluminate the structure of the retractor assembly. The remainingstructures of FIG. 4 show the use of respective patterns on the seatbelt assembly as discussed above. The components may include, but arenot limited to, a seat belt retractor assembly (i.e., a spool thatunwinds and re-winds the seat belt into a webbing payout section (44)),a payout aperture (30) through which a seat belt extends, a portion of aseat belt assembly configured as a shoulder strap (48), a lap strap(36), a lap belt anchor (32), web length adjustment hardware (34), abuckle (40), buckle hardware (35), a seat belt tongue (42), at least oneface (46) of the seat belt buckle (40), and peripheral hardware used toinstall or enable the seat belt assembly functions (e.g. d-rings,retention buttons). A shoulder strap (48) has a first shoulder strappattern (38) on one side that can be identified as stripes and a secondshoulder strap pattern (50) on an opposite side. In the example of FIG.3, the opposite side of the shoulder strap is also visible as a lap beltpattern (50) for an associated lap strap (36). The buckle (40), thetongue (42), buckle faces (46), and web length adjustment hardware (34)are all viable candidates for having an identifiable pattern thereon.The structures in the image and the associated patterns provide data toaccomplish multiple functions—particularly classifying occupantspursuant to an associated occupant classification system (“OCS”) (21),calculating spatial measurements relative to known references within thevehicle, and tracking movement within the vehicle. One goal is toidentify that a lap strap and shoulder belt for the seat belt assemblycross an occupant at correct locations on the torso (65) to achieve aproper buckled/unbuckled state from sensors in the buckle.

The occupant classification system (“OCS”) (21) may include numerouskinds of hardware, position sensors, pressure sensors, weight sensors,and the like to identify a vehicle occupant so that a vehicle meetsregulatory requirements. Many traits of an occupant are currentlyidentified by an OCS to assist in controlling air bag deployment as wellas other restraint systems, alerts, and operational control signals. Innon-limiting embodiments of this disclosure, images gathered pursuant tothe methods and systems herein may be used in conjunction with an OCS toidentify proper seat belt placement for many different levels of humandevelopment (e.g., adult, child, infant) as well as anatomy structures(large male, average male or female, small female). Optimal seat beltplacement for these diverse occupants will be significantly differentfor each. An OCS may receive data from the computerized imaging systemsdescribed herein to conduct edge analyses to detect occupant forms, 3-Ddepth analyses for torso position, and anatomical dimensioning for seatbelt confirmation relative to the occupant's body. Single camera andmulti-camera systems for both seat belt monitoring and occupantclassification are well within the scope of this disclosure.

FIGS. 5 and 6 illustrate an example of a three-dimensional analysis of avehicle occupant in a vehicle seat (13) and utilizing the above notedcomponents of the seat belt assembly (20). An image as shown may beconstructed with sufficient levels of detail to distinguish patterns onnumerous components of the seat belt assembly (such as the differentpatterns (48, 50) on the shoulder strap (38) and lap strap (36)). Thecomponents of the seat belt assembly as well as the occupant's body isshown with sufficient clarity to model the interior of the vehicle atthis seat (i.e., at this region of interest) in a three dimensionalcoordinate system. Such mapping to a coordinate system allows forcomputer software to calculate spatial measurements for each frame of animage as well as tracking motion across pairs of images. In thenon-limiting example of FIG. 5, a computerized method implemented by thesystem disclosed herein calculates numerous angles useful in identifyingproper seat belt use or improper seat belt use. The spatial measurementsmay include distances from a camera (12) to a portion of the occupant'sbody (i.e., torso receiving a shoulder strap), distances betweencomponents of the seat belt assembly (20) and portions of the occupant'sbody, and angles between structures within the vehicle, the occupant'sbody, and the seat belt assembly. For example, without limiting thisdisclosure, FIG. 5 illustrates a method of calculating a first angle(Theta 1) between an occupant's shoulder and a longitudinal axis alongthe seat belt, a second angle (Theta 2) between the longitudinal axis ofthe seat belt and a referenced horizontal axis for the coordinatesystem, a third angle (Theta 3) calculated between a portion of theoccupant's head and the longitudinal axis of the seat belt. These kindsof static measurements are mere examples of the system gathering datapoints to use in determining beginning, intermediate, and finalpositions of seat belt components in a respective vehicle. This data canthen be used to prepare and issue associated alerts or warnings to theoccupants, control air bags and other restraint systems, and update datato help an OCS verify classifications of occupants in the vehicle.

FIG. 6 illustrates the image of FIG. 5 with the addition of an obscuringobject (33) placed in the lap of an occupant. The obscuring object maybe a blanket, cargo, food, pets, or any item that hides a portion of theseat belt assembly from view in the image. In this scenario, the methodsand systems disclosed herein use the above described spatialmeasurements and angles along with available views of the seat beltcomponents that have not been obscured to predict seat belt position.The system may utilize additional angle measurements for components thatare readily discernible in the image. One aspect of this disclosureincludes preparing patterns of known reflectivity and luminance on seatbelt components and other structures in the vehicle to provide numerousavenues of calculating seat belt position from areas that are most oftenunobstructed during use. For example, the payout aperture (30) andaperture pattern (52) would still be readily available in the image asshown in FIG. 6 to calculate Theta 5 as the angle between a webbingpayout section (44) along an area of a b pillar of the vehicle and aseat belt payout exiting the payout aperture (30). Similarly, the angle(Theta 6) between a shoulder strap (48) and a lap strap (36) remainsdiscernible along the buckle region (40) of the seat belt assembly. Byassociating the reflective patterns in strategic locations relative tocameras (12) installed in the vehicle interior (10), the system willgather sufficient image data from unobstructed regions to confirm seatbelt use and placement.

FIG. 7 illustrates the kinds of analyses that are available with theapparatuses illustrated in FIGS. 2-4 and the pattern placement of FIGS.5-6. The computer of this disclosure may be installed in the vehicle ina way that allows for the initial image of FIG. 7A to be compiled as a3-D image and to provide extractable pattern data from a seat beltcomponent as shown in FIG. 7B. Afterwards, both two dimensional andone-dimensional analyses of the spectrum, as reflected back to an imagesensor used in the vehicle is available for data processing tools. FIG.7 illustrates a cross correlation algorithm use to confirm an x, y, zposition of a seat belt pattern across an occupant's chest.

Similarly, FIG. 8A shows another embodiment of a camera (12), utilizinginfrared or near infrared light sources (16) to illuminate a vehicleinterior (10) and provide reflective light signals back to a imagesensor (14). In FIG. 8B, reference points within the vehicle have beenidentified as fixed reference apertures (70A, 70B, 70C) installed infixed locations along the ceiling of a vehicle. A reference target (forexample fixed reference aperture 70C) has been selected at a knowndistance from the camera and a known pixel location relative to thecamera imager. This configuration sets up a way to utilize moresophisticated machine vision techniques, initially by calculating simplereference positions from the camera (12) to the fixed referenceapertures (payout apertures having pre-determined pattern appliques)(70A, 70B, 70C) as shown in FIG. 8E.

Setting up the fixed reference apertures (70) and their respective depthmeasurements (from fixed camera (12) location and payout aperture (30)location) allows the system to account for both fixed structures in thevehicle as well as dynamic (i.e., moving, or adjustable) structures inthe vehicle. The fixed and dynamic structures can be used in measurementand motion analyses and still maintain a high confidence level in theimage data. For example, and without limiting the disclosure in any way,a seat (13) in a vehicle may be movable along a track in a longitudinaldirection (e.g., moving a driver's seat either away from or toward asteering wheel (19)) and have an angular range of motion for tiltingboth a seat back and a bottom cushion. FIG. 9 illustrates that a seat(13) installed in numerous vehicles includes at least two positions asshown (and most likely dozens more, given the adjustable structures thatare common in seat assemblies). By identifying fixed reference aperturesas points of reference (FIG. 8, Refs. 70A, 70B, 70C) within the vehicleinterior (10), such as the above described payout apertures (30), a seatbelt monitoring system can use the fixed reference points (70) as apoint of origin to take additional measurements of vehicle componentsthat are adjustable within a known range of motion. Also, fixed pointsof reference cannot move relative to the camera imager and can bedesigned with a fixed reflective intensity, noise removal algorithmsutilizing the common noise components of light received from these fixedreferences can be applied to reduce reflective intensity and/or distancenoise. FIG. 9 illustrates that a reference vector (R1) may beconstructed as a part of the 3-D coordinate modeling for the vehicleinterior. Accordingly, other reference points (80A-D) in an associatedimage may be identified, and distances from the first reference (70) canbe established for other marked references that bear a reflectivepattern as described above for FIGS. 1-6. Even when a vehicle structuresuch as a seat (13) has adjustable positions, the limited number ofpossible positions and the defined range of motion for the seat, orother adjustable structure in the vehicle, accommodates anidentification as to which of the possible positions the structure hasassumed in any one image.

With these known values established, the pattern recognition, 3-Dreconstruction, spatial measurement and movement tracking methods areenabled for comparative analysis. FIGS. 10-13 illustrate this conceptfurther in regard to a seat belt buckle (40) that has been fitted withthe above described patterns for luminance and image analysisrecognition. In FIG. 11, a camera (12) as described above includes theseats (13) and seat belt buckles (40) in the camera field of view. Eventhough the seat, and therefore the buckle as well, are dynamiccomponents, their adjustable ranges are limited and known pursuant toOEM specifications. The computer program logic described herein,therefore, can determine with a high degree of certainty where variousreference points on the dynamic structures are positioned within thevehicle at the time of any frame of a series of images. This procedureimproves accuracy for both an occupant classification determination andseat belt monitoring as described above.

Without limiting this disclosure to any one particular analysis, FIGS.13-18 and FIGS. 20-23 illustrate how the seat belt monitoring system andassociated algorithms utilized by associated computers can showengineers, designers, and operators intricate trends in one dimensional,two dimensional, and three dimensional data formats. The embodiments ofthis disclosure also benefit from computer processing techniquesimplemented in computerized software that include programmed noiseremoval algorithms utilizing the common noise components of lightreceived from the respective patterns.

The above-described disclosure has described apparatuses and techniquesfor (i) establishing identifiable patterns associated with a seat beltassembly and corresponding vehicle structures and (ii) providing imagingtechniques that incorporate known reference values under numerousconditions, in regard to both fixed and dynamic structures within avehicle. Structures in a vehicle may be either fixed or dynamic atdifferent times. In one sense, certain components considered to be fixedin a vehicle include the fixed components of the seat belt assembly suchas at least one of a webbing payout section (44) that defines a seatbelt payout aperture, a seat belt buckle, a first anchor point for saidseat belt buckle, a second anchor point for a lap strap portion of theseat belt assembly, and peripheral hardware connected to the fixedcomponents. Dynamic components may include at least one of a seat beltextending from an aperture in a seat belt retractor, a shoulder strapportion of said seat belt, a lap belt portion of said seat belt, and aseat belt tongue because these items are likely to move during use andbe in different positions from one occupant to another. Other componentsmay have limited ranges of motion as described above (e.g., a seat or aseat belt buckle) so that while being adjustable in a dynamic sense,that same component can serve as a fixed component reference point if aselected position is known.

Using multiple cameras, multiple reference points, and properly placedpatterns of distinct reflectivity accommodates a system that not onlyprovides static spatial measurements of distances and angles, but alsoprovides movement information for an occupant or a vehicle structurerelative to a known or calculated reference point.

The iterative frames of FIG. 19 illustrate using these techniques for atime series motion analysis of an occupant interacting with a seat beltpayout from a reference point (70) such as a seat belt payout aperture(30) having a predetermined pattern (52). With these reference pointsand associated measurements and images, the system is adapted to accountfor numerous occupant positions (i.e., lying down versus sittingnormally) and adjust calculations for proper seat belt use accordingly.In one embodiment, the reference points (70) can be used with imaginganalysis to identify a seat belt pattern showing seat belt slack acrossan occupant that is not suitable for proper and safe seat belt use.

Successive images from the at least one camera are analyzed to trackoccupant motion within a region of interest, wherein the motion isrelative to at least one of the fixed components in the vehicle.Occupant motion data derived from the images is utilized by theprocessor to track occupant physiological processes, including but notlimited to at least one of breathing, respiration rate, heart rate,mouth opening and closing, blinking, and speech patterns. Some of thesemeasurements may be validated by the processor further calculating aseat position within the region of interest relative to the referencemeasurement of the fixed component.

Although the present disclosure has been described in detail withreference to particular arrangements and configurations, these exampleconfigurations and arrangements may be changed significantly withoutdeparting from the scope of the present disclosure. For example,although the present disclosure has been described with reference toparticular communication exchanges involving certain network access andprotocols, network device may be applicable in other exchanges orrouting protocols. Moreover, although network device 102 has beenillustrated with reference to particular elements and operations thatfacilitate the communication process, these elements, and operations maybe replaced by any suitable architecture or process that achieves theintended functionality of network device.

Numerous other changes, substitutions, variations, alterations, andmodifications may be ascertained to one skilled in the art and it isintended that the present disclosure encompass all such changes,substitutions, variations, alterations, and modifications as fallingwithin the scope of the appended claims. The structures shown in theaccompanying figures are susceptible to 3-D modeling and can bedescribed relative to vertical, longitudinal and lateral axesestablished with reference to neighboring components as necessary.

Note that in this Specification, references to various features (e.g.,elements, structures, modules, components, steps, operations,characteristics, etc.) included in “one embodiment”, “exampleembodiment”, “an embodiment”, “another embodiment”, “some embodiments”,“various embodiments”, “other embodiments”, “alternative embodiment”,and the like are intended to mean that any such features are included inone or more embodiments of the present disclosure, but may or may notnecessarily be combined in the same embodiments. Note also that an“application” as used herein this Specification, can be inclusive of anexecutable file comprising instructions that can be understood andprocessed on a computer, and may further include library modules loadedduring execution, object files, system files, hardware logic, softwarelogic, or any other executable modules.

In example implementations, at least some portions of the activities maybe implemented in software provisioned on networking device 102. In someembodiments, one or more of these features may be implemented incomputer hardware, provided external to these elements, or consolidatedin any appropriate manner to achieve the intended functionality. Thevarious network elements may include software (or reciprocatingsoftware) that can coordinate in order to achieve the operations asoutlined herein. In still other embodiments, these elements may includeany suitable algorithms, hardware, software, components, modules,interfaces, or objects that facilitate the operations thereof.

Furthermore, computer systems described and shown herein (and/or theirassociated structures) may also include suitable interfaces forreceiving, transmitting, and/or otherwise communicating data orinformation in a network environment. Additionally, some of theprocessors and memory elements associated with the various nodes may beremoved, or otherwise consolidated such that single processor and asingle memory element are responsible for certain activities. In ageneral sense, the arrangements depicted in the Figures may be morelogical in their representations, whereas a physical architecture mayinclude various permutations, combinations, and/or hybrids of theseelements. It is imperative to note that countless possible designconfigurations can be used to achieve the operational objectivesoutlined here. Accordingly, the associated infrastructure has a myriadof substitute arrangements, design choices, device possibilities,hardware configurations, software implementations, equipment options,etc.

In some of example embodiments, one or more memory elements (e.g.,memory can store data used for the operations described herein. Thisincludes the memory being able to store instructions (e.g., software,logic, code, etc.) in non-transitory media, such that the instructionsare executed to carry out the activities described in thisSpecification. A processor can execute any type of computer readableinstructions associated with the data to achieve the operations detailedherein in this Specification. In one example, processors (e.g.,processor) could transform an element or an article (e.g., data) fromone state or thing to another state or thing. In another example, theactivities outlined herein may be implemented with fixed logic orprogrammable logic (e.g., software/computer instructions executed by aprocessor) and the elements identified herein could be some type of aprogrammable processor, programmable digital logic (e.g., a fieldprogrammable gate array (FPGA), an erasable programmable read onlymemory (EPROM), an electrically erasable programmable read only memory(EEPROM)), an ASIC that includes digital logic, software, code,electronic instructions, flash memory, optical disks, CD-ROMs, DVD ROMs,magnetic or optical cards, other types of machine-readable mediumssuitable for storing electronic instructions, or any suitablecombination thereof.

These devices may further keep information in any suitable type ofnon-transitory storage medium (e.g., random access memory (RAM), readonly memory (ROM), field programmable gate array (FPGA), erasableprogrammable read only memory (EPROM), electrically erasableprogrammable ROM (EEPROM), etc.), software, hardware, or in any othersuitable component, device, element, or object where appropriate andbased on particular needs. Any of the memory items discussed hereinshould be construed as being encompassed within the broad term ‘memoryelement.’ Similarly, any of the potential processing elements, modules,and machines described in this Specification should be construed asbeing encompassed within the broad term “processor.”

The invention claimed is:
 1. A system of evaluating seat belt assembliesinstalled in a vehicle, comprising: at least one camera connected to acomputer system and at least one light source that illuminates regionsof interest within a vehicle, wherein at least one region of interest iswithin the at least one camera's field of view; at least one seat beltassembly installed in the vehicle and positioned within the at least onecamera field of view, said seat belt assembly comprising fixedcomponents that are stationary in the vehicle and dynamic componentsthat move within the vehicle, said fixed and dynamic componentscomprising respective patterns that each have a predeterminedreflectivity, wherein the computer system comprises at least oneprocessor connected to memory having computer implemented instructionsthereon, the computer implemented instructions configured to: use thecamera to generate at least one image of the at least one region ofinterest in the vehicle; identify at least one fixed component of the atleast one seat belt assembly as a reference component within the imageof the region of interest; calculate at least one reference measurementas the distance between the camera and an identified pattern in theimage as reflected from the reference component; calculate respectivespatial measurements of dynamic components of the seat belt assembly ascaptured in the image, wherein the respective spatial measurements ofthe dynamic components comprise distances between selected patternsreflected from the dynamic components as shown in the image and otherstructures within the vehicle also shown in the image; and compare thespatial measurements of the dynamic components of the seat belt assemblyrelative to the reference measurement to evaluate the seat belt assemblyin the vehicle.
 2. A system according to claim 1, wherein the fixedcomponents of the seat belt assembly comprise at least one of a webpayout section that defines a payout aperture; a seat belt buckle, afirst anchor point for said seat belt buckle, a second anchor point fora lap strap portion of the seat belt assembly, and peripheral hardwareconnected to said fixed components.
 3. A system according to claim 1,wherein said dynamic components comprise at least one of a seat beltextending from an aperture in a seat belt retractor, a shoulder strapportion of said seat belt, a lap belt portion of said seat belt, and aseat belt tongue.
 4. A system according to claim 1, wherein multiplefixed components of the seat belt assembly are designated by thecomputer system as reference components in the image, and the computerimplemented instructions are configured to measure spatial positions ofpoints in the image relative to the reference components.
 5. A systemaccording to claim 4, wherein the reference measurement is a depthreference measurement and the respective spatial measurements are depthmeasurements of the respective patterns on dynamic components of theseat belt assembly as captured in the image.
 6. A system according toclaim 4, wherein the multiple fixed components comprise respectivelydistinct patterns having individualized reflectivity.
 7. A systemaccording to claim 1, wherein the system comprises at least two cameraseach constructing images of the region of interest, and a pair of imagescomprises one image from each of the at least two cameras, whereinspatial measurements are taken across the pair of images and providedata to an occupant classification system connected to the computersystem.
 8. A system according to claim 7, wherein the occupantclassification system comprises additional computerized instructionsconfiguring the processor to detect body shapes, body edges, bodydepths, body dimensions, and body positions for occupants in the regionof interest.
 9. A system according to claim 8, wherein successive imagesfrom the at least two cameras are analyzed to track occupant motionwithin the region of interest, wherein said motion is relative to atleast one of the fixed components in the vehicle.
 10. A system accordingto claim 9, wherein occupant motion data derived from the images isutilized by the processor to track occupant physiological processes. 11.A system according to claim 10, wherein the physiological processescomprise at least one of breathing, mouth opening and closing, blinking,and speech.
 12. A system according to claim 1, wherein the processorfurther calculates a seat position within the region of interestrelative to the reference measurement of the fixed component.
 13. Asystem according to claim 1, further comprising establishing a dynamiccomponent of the seat belt assembly system as a second referencecomponent, wherein the second reference component has a defined range ofmotion constrained to known positions, wherein the processor calculatesthe known position for the second reference component as captured in theimage.
 14. A system according to claim 13, wherein the processorcalculates vectors from the second reference component to the camera ascaptured by the image to derive position information for the secondreference component.
 15. A system according to claim 14, wherein thesecond reference component comprises at least one of a point on avehicle seat and a seat belt buckle connected to the vehicle seat suchthat the seat belt buckle has limited ranges of motion relative to thevehicle seat.
 16. A system according to claim 1, wherein the cameraconstructs a sequence of images to compare and detect motion of at leastone dynamic component of the seat belt assembly, wherein spatialmeasurements are taken across frames of the sequence to track use of adynamic component in the vehicle.
 17. A system according to claim 16,wherein the spatial measurements comprise depth measurements of a seatbelt payout as the dynamic component relative to a payout aperture asthe fixed component, and wherein said depth measurements track seat beltpayout over an occupant torso.
 18. A system according to claim 17,further comprising a buckle switch to provide the processor with abuckled/unbuckled signal to confirm seat belt use.
 19. A systemaccording to claim 16, wherein the processor uses the sequence of imagesto compare and detect motion of an occupant in the region of interest bycomparing occupant position depth measurements relative to the referencecomponent.
 20. A system according to claim 19, wherein the processoruses the sequence of images to compare and detect depth measurements ofa seat belt payout relative to a depth of a torso of the occupant, usingthe reference component for a known distance, and determining seat beltslack against the torso.